Evidence map›Paper›PMID 42734018›Full record

ArticleChembiochem : a European journal of chemical biology2026

An Engineered β-Aminopeptidase With Better Product Selectivity for L-Carnosine Production.

Bi-Han Guan, Wu-Tong Yin, Chen Zhao, Jiang Pan, Jian-He Xu

Abstract read
In one paragraph

Article in Chembiochem : a European journal of chemical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bi-Han GuanState Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai, China.
Wu-Tong YinState Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai, China.
Chen ZhaoState Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai, China.ORCID https://orcid.org/0000-0001-8871-542X
Jiang PanState Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai, China.
Jian-He XuState Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai, China.ORCID https://orcid.org/0000-0003-4301-7630

Funding

National Key Research and Development Program of China 2024YFA0917800National Natural Science Foundation of China 22478116Science and Technology Commission of Shanghai Municipal Government 24HC2810300Science and Technology Commission of Shanghai Municipal Government 25HC2810400Science and Technology Commission of Shanghai Municipal Government Major Project
6 · The paper itself

Abstract

Efficient enzymaticsynthesis of L-carnosine (L-Car) is often limited by competing hydrolysis and side reactions that reduce substrate utilization and product yield. In this study, a β-aminopeptidase (CbAP) from Caulobacter sp. was systematically engineered to enhance catalytic selectivity toward L-Car using β-alaninamide and L-histidine as substrates. Analysis of β-alaninamide-derived byproducts revealed two major competing pathways, namely β-alaninamide hydrolysis and self-ligation into short oligopeptides. To evaluate the balance between L-Car synthesis and competing reactions, a composite apparent selectivity index (R

Indexed as

AminopeptidasesProtein EngineeringCatalytic DomainModels, MolecularSubstrate SpecificityAminopeptidasesbiocatalysiscatalytic selectivityL‐carnosineprotein engineeringside reaction suppressionβ‐aminopeptidase

Identifiers

PMID42734018
PMCPMC13572960

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.